Image compression/decompression system employing pixel thinning-out and interpolation scheme

ABSTRACT

An improved image thinning-out processing scheme includes processes of performing pixel thinning-out operation and compressing image data; and determining a position of pixel to be thinned out along a first direction depending on the position thereof along a second direction perpendicular to the first direction.

BACKGROUND OF THE INVENTION

[0001] 1. Field of the Invention

[0002] The present invention generally relates to an imagecompression/decompression system, in particular, to an imagecompression/decompression system employing efficient pixel thinning-outand interpolation schemes.

[0003] An image compression/decompression system according to thepresent invention may be applied widely to various image processingapplication programs, various device drivers (software) such as printerdrivers, also, to various image processing apparatus/equipmentprocessing color images.

[0004] 2. Description of the Related Art

[0005] With regard to image compression/decompression techniques,various schemes have been proposed. For example, Japanese laid-openpatent application No. 7221993 discloses a color image data thinning-outmethod, and a color image data compression method. In the methods,according to change rates in U data and V data representing colorcomponents, a size of pixel zone to be thinned out for each image blockis controlled. Specifically, as the change rate is larger, the size ofpixel zone to be thinned out is to be reduced. On the other hand, as thechange rate is smaller, the size of pixel zone to be thinned out is tobe enlarged. Thereby, an edge line of an image is prevented from beinglost due to thinning-out processing.

[0006] Thus, by utilizing a characteristic of human eyes, a thinning-outrate is appropriately selected for a color component according to acolor change rate for each image block such as that including 8×8pixels, 16×16 pixels or the like. Thereby, effective image compressionwithout remarkable apparent degradation in image quality may beattained.

[0007] However, according to the above-described methods disclosed byJapanese laid-open patent application No. 7-221993, a considerable timemay be required for calculating change rates in U data and V data foreach image block.

[0008] Furthermore, generally speaking, a natural image is likely toinclude a lot of thin lines/edge lines extending horizontally orvertically while a few of those extending obliquely. Therefore, whensimply pixels arranged vertically are thinned out as disclosed by theabove-mentioned patent publication as shown in FIG. 1, a lot of thinlines, edge lines and so forth included in a natural-image may becompletely lost during image data compressing processing.

SUMMARY OF THE INVENTION

[0009] An object of the present invention is to solve theabove-mentioned problem, and, to provide an imagecompression/decompression schemes having a pixelthinning-out/interpolation schemes, by which, efficient image datacompression/decompression can be attained by an effectively reduced dataprocessing time, reduced data processing resources, but withoutremarkable apparent degradation in image quality during image datacompression/decompression processing.

[0010] For this purpose, according to the present invention, as shown inFIG. 2, pixels to be thinned out are determined to be those arrangedobliquely or in a staggering manner, not straightly vertically orhorizontally. Thereby, it is possible to prevent a lot of thin lines,edge lines and so forth extending horizontally or vertically included ina natural image from being lost through image data compressingprocessing.

[0011] Furthermore, by selecting pixels to be thinned out as shown inFIG. 4 in a staggering manner, in comparison to a case shown in FIG. 3,distances between adjacent ones of the pixels to be thinned out becomeeffectively elongated. Thereby, it is possible that, even whenvertically extending thin lines included in a natural image are lostpartially by the thinning-out processing, this may not result inremarkable apparent degradation of image quality.

[0012] In order to achieve such thinning-out processing obliquely or ina staggering manner, a position of a pixel to be thinned out for eachimage block is determined, according to a predetermined rule, in such amanner that the pixels thinned out are prevented from becoming adjacentto each other between image blocks adjacent to each other vertically andhorizontally. Thereby, it is possible to achieve thinning-out processingobliquely or in a staggering manner by a simple configuration either ona device (LSI or the like) or on a software program.

[0013] An image compressing scheme according to the present inventioncomprising:

[0014] performing pixel thinning-out operation and compressing imagedata; and

[0015] determining a position of pixel to be thinned out along a firstdirection depending on the position thereof along a second directionperpendicular to the first direction.

[0016] Thereby, it is possible to prevent thin lines/edge lines includedin an original image from being lost remarkably apparently whilehigher-rate data compressing can be attained with a relatively simpleconfiguration.

[0017] In the above-mentioned scheme, the position of pixel to bethinned out may comprise a position with respect to each predeterminedunit area of the relevant image including a predetermined number ofpixels.

[0018] Thus, by performing image data compression processing for eachunit area of the relevant original image, it is possible to attain highspeed compression processing.

[0019] In the scheme, the positions of pixels to be thinned out alongthe first direction may be determined along the second direction suchthat the positions of pixels to be thinned out do not align with oneanother between each pair of unit areas adjacent to one another alongthe second direction.

[0020] Control operation performing such a manner of processing may beeasily attained by configuring such that the positions of thethinned-out pixels with respect to the respective unit areas may bechanged alternately every line of unit areas according to a simple rule,as shown in FIGS. 6A, 6B, 7, 8 and 9. Thus, the positions of thethinned-out pixels are located not continues but intermittently, and,thus, it is possible to effectively prevent thin lines/edge linesincluded in an original image from being lost continuously. Thus, a highimage quality may be maintained even through image data compressing anddecompressing processes.

[0021] An image decompressing scheme according to the present inventioncomprises:

[0022] interpolating/generating thinned-out pixels; and

[0023] determining pixels to be used for the interpolation, whereinpixels nearest to the thinned-out pixels may be selected for theinterpolation.

[0024] Thereby, high speed image decompressing processing may beattained while a high image quality may be maintained through image datacompressing and decompressing processes.

[0025] In the scheme, pixels not included in an original pixel block inwhich thinned-out pixels are included may be applied forinterpolation/generation of the thinned-out pixels.

[0026] Thereby, it is possible to utilize pixels of various pixel blocks(located in various directions, particularly, vertical and horizontaldirections) for interpolation. Accordingly, thin lines/edge linesextending in various directions included in an original image may beeffectively prevented from being lost during image datacompressing/decompressing processing.

[0027] The pixel to be used for interpolation may be determined suchthat pixels adjacent to an original pixel block (rectangular block) viashort sides thereof may be applied.

[0028] Thereby, it is possible to utilize pixels of various pixel blocks(located in various directions, particularly, vertical and horizontaldirections) for interpolation. Accordingly, thin lines/edge linesextending in various directions included in an original image may beeffectively prevented from being lost during image datacompressing/decompressing processing.

[0029] Another image decompressing scheme according to the presentinvention comprises:

[0030] performing interpolation of thinned-out pixels; and

[0031] determining a method of interpolation according to a pixel-numberchanging rate of pixel-number changing processing performed after theinterpolation such that a finer interpolation method be selected as thepixel-number changing rate at which the number of pixels is increasedbecomes larger.

[0032] Thereby, high speed decompressing processing may be attained,while a high image quality may be maintained during image datacompressing/decompressing processing.

[0033] In the scheme, a nearest pixel method (described later) may beapplied when the pixel-number changing rate is less than a firstthreshold, a linear interpolation method (well-known) is applied whenthe pixel-number changing rate falls within a range between the firstthreshold and a second threshold, and a three-order interpolation method(described later) is applied when the pixel-number changing rate is morethan the second threshold.

[0034] Thereby, it is possible to appropriately select an interpolationmethod according to a size of image to be output afterinterpolation/decompression. In case merely a small image should bedisplayed as an output image, a less finer interpolation method may beapplied so that a time required for performing image datadecompression/interpolation may be effectively reduced. In contrastthereto, in case a relatively large image should be displayed, a finerinterpolation method may be applied so that remarkable image degradationthrough image data compression which is likely to be apparent in such acase may be effectively prevented.

[0035] Another image decompressing scheme according to the presentinvention comprises:

[0036] interpolating thinned-out pixels from not-thinned-out pixels; and

[0037] determining an interpolating method applied,

[0038] so that a less finer interpolation method may be applied forthinned-out pixels located nearer to the not-thinned-out pixels used forthe interpolation.

[0039] Thereby, high speed decompressing processing may be attained,while a high image quality may be maintained during image datacompressing/decompressing processing.

[0040] In the scheme, a plurality of interpolation methods may beselectively applied for a single image and the interpolation method tobe applied may be determined according to the center-to-center pixeldistances from the not-thinned-out pixels.

[0041] Thereby, high speed decompressing processing may be attained,while a high image quality may be maintained during image datacompressing/decompressing processing.

[0042] The nearest pixel method may be applied for thinned-out pixelsmost nearest to the not-thinned-out pixels used for interpolation, andat least one of the linear interpolation method and third-orderinterpolation method may be applied for the other thinned-out pixels.

BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Other objects and further features of the present invention willbecome more apparent from the following detailed description when readin conjunction with the following accompanying drawings:

[0044]FIG. 1 illustrates a state of image data thinning-out processingscheme in the related art;

[0045]FIGS. 2, 3 and 4 illustrate basic concepts of image datathinning-out processing schemes according to the present invention;

[0046]FIG. 5 illustrates a block diagram of an image processing systemto which first through sixteenth embodiments of the present inventionmay be applied;

[0047]FIGS. 6A and 6B illustrate an image data thinning-out processingscheme according to a first embodiment of the present invention;

[0048]FIG. 7 illustrates an image data thinning-out processing schemeaccording to a second embodiment of the present invention;

[0049]FIG. 8 illustrates an image data thinning-out processing schemeaccording to a third embodiment of the present invention;

[0050]FIG. 9 illustrates an image data thinning-out processing schemeaccording to a fourth embodiment of the present invention;

[0051]FIG. 10 illustrates processing illustrated with reference to FIGS.6A and 6B;

[0052]FIG. 11 illustrates processing of image data interpolation forinterpolating pixels thinned out as illustrated with reference to FIGS.6A and 6B;

[0053]FIG. 12 illustrates processing illustrated with reference to FIG.8;

[0054]FIG. 13 illustrates processing illustrated with reference to FIG.9;

[0055]FIG. 14 illustrates a basic image data interpolation patternaccording to a fifth embodiment of the present invention;

[0056]FIGS. 15A through 15C illustrate various types of definition ofadjacent pixels for illustrating the present invention;

[0057]FIGS. 16 and 17 illustrate specific interpolation processingexamples according to the fifth embodiment of the present invention;

[0058]FIG. 18 illustrates a basic image data interpolation patternaccording to a sixth embodiment of the present invention;

[0059]FIG. 19 illustrates a specific interpolation processing examplesaccording to the sixth embodiment of the present invention;

[0060]FIG. 20 illustrates a basic image data interpolation patternaccording to a seventh embodiment of the present invention;

[0061]FIG. 21 illustrates a specific interpolation processing examplesaccording to the seventh embodiment of the present invention;

[0062]FIG. 22 illustrates a basic image data interpolation patternaccording to an eighth embodiment of the present invention;

[0063]FIG. 23 illustrates a specific interpolation processing examplesaccording to the eighth embodiment of the present invention;

[0064]FIGS. 24 and 25 illustrate a case where image data is enlarged insize (the number of pixels) after decompression/interpolation isperformed;

[0065]FIG. 26 illustrates processing described with reference to FIGS.18 and 19;

[0066]FIG. 27 illustrates processing described with reference to FIGS.24 and 25; and

[0067]FIGS. 28 through 35 illustrate processing according to ninththrough sixteenth embodiments of the present invention.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0068] Referring to the drawings, an image compressing/decompressingapparatus which realizes an image compressing/decompressing methodaccording to the present invention will now be described. In addition,this image compressing/decompressing method is realizable also on aninformation recording medium storing a software program which isexecuted by a general-purpose computer as will be described.

[0069]FIG. 5 is a circuit block diagram showing an example of aconfiguration of an image compressing/decompressing apparatus whichrealizes an image compressing/decompressing method according to thepresent invention.

[0070] As shown in FIG. 5, a printer apparatus 30 which carries outprinting output image data read out from a hard disk drive unit HDD 10which stores original image data is connected with a personal computerPC 20 which performs image compression processing, and images havingundergone the image processing by the PC 20 is transferred to theprinter apparatus 30 via a data bus 40.

[0071] In a random access memory RAM 1 (21) image data read out from thehard disk drive unit HDD 10 is written, so that the personal computer PC20 may perform image compression thereon. A CPU 1 (22) manages andcontrols the entire personal computer PC 20. By using a random accessmemory RAM 2 (31), a CPU 2 (32) of the printer apparatus 30 performsimage data decompressing operation on image data. The CPU2 manages andcontrols the entire printer apparatus 30.

[0072] When original image data stored in the hard disk drive unit HDD10 is to be printed out by the printer apparatus 30, the original imagedata is compressed by the personal computer PC 20, and the compressedimage data is transmitted to the printer apparatus 30 through the databus 40. By the image compression processing, since the amount oftransmitting data to the printer apparatus 30 is reduced, thetransmitting time is shortened, and even considering the time requiredfor image compression and image decompressing of the original imagedata, high-speed print-out operation becomes realizable.

[0073] First, the original image data recorded in the hard disk driveunit HDD 10 is read out by the CPU 1 (22) of the personal computer PC20, and is written into a reading area 21 a of the random access memoryRAM 1 (21) according to instructions given by the CPU 1 (22).

[0074] The CPU 1 (22) reads out the original mage data from the randomaccess memory RAM 1 (21) appropriately, and performs image compressionprocessing thereon accordingly.

[0075] The CPU 1 (22) writes the thus-compressed data into a compressionarea 21 b of the random access memory RAM 1 (21), and stores theretemporarily.

[0076] After that, the CPU1 (22) gives instructions to the random accessmemory RAM 1 such that the compressed data is read out therefrom, and,via the data bus 40, it is transferred to the random access memory RAM 2(31) in the printer apparatus 30, and, is written to a transfer area 31a thereof.

[0077] The CPU 2 (32) of the printer apparatus 30 reads out thecompressed data from the transfer area 31 a of the random access memoryRAM 2 (31), obtains decoding values therefrom, performs decompressingprocessing on the compressed image data, and thus, reproduces adecompressed image having the number of pixels same as that of theoriginal image data.

[0078] Then, the CPU 2 32 writes the decompressed image data into adecompression area 31 b of the random access memory RAM 2 (31), andstores there, temporarily.

[0079] Then, the CPU2 32 reads out the decompressed data from the randomaccess memory RAM 2 (31), and, through predetermined processes, thedecompressing image data is printed out on a print paper.

[0080] The predetermined processes may include a size-change process bywhich the number of pixels of the image data is changed according toinstructions given by a user or the like.

[0081] The image compression processing carried out by the personalcomputer 20 and the image decompressing processing carried out by theprinter apparatus 30 will now be described based on FIGS. 6A and 6Bfirst, and then, following figures, in sequence.

[0082]FIG. 6A illustrates a concept of a process of compressing an imageblock of 2×3 pixels into an image block of 2×2 pixels. FIG. 6Billustrates a state of thin lines A and B included in an original imageaffected by the above-mentioned compression operation.

[0083] In this example, as shown in the figures, an image block oforiginal image (original block), from which pixels are thinned out, hasn pixels vertically and m pixels horizontally, and, thus, has n×mpixels. Further, an image block which is thinned out from theabove-mentioned image block (thinning-out block) of original image has npixels vertically, and x pixels horizontally, and thus, has n×x pixels.Then, a compressed block obtained after the compression (compressedblock) has n pixels vertically, and (m−x) pixels horizontally, and,thus, has n×(m−x) pixels.

[0084] As shown in FIGS. 6A and 6B, in this example, n=2, m=3, x=1.Thus, from the original block of 2×3 pixels, the thinning-out block of2×1 pixels is thinned out, and, then, the compressed block of 2×2 pixelsremains.

[0085] Specifically, as shown in the figures, according to the presentinvention, a position of the thinning-out block with respect to theoriginal block is changed alternately along the vertical direction. Inthe example shown in the figures, on a first line, the thinning-outblock is located at the left end of the original block, then, on asecond line, differently, the thinning-out block is located at the rightend of the original block, then, on a third line, the left end, Thus,the position of the thinning-out block with respect to the originalblock is determined depending on the position along the verticaldirection.

[0086] Thus, above-mentioned thinning-out processing by an obliquemanner or staggering manner can be attained, as shown in the figures.Thereby, as shown in FIG. 6B, pixels on the thin lines or edge lines A(vertically extending) and B (horizontally extending) are lost bythinning-out processing only partially, so that the original image maybe prevented from being remarkably apparently degraded.

[0087]FIGS. 6A and 6B illustrate the example in which the thinning-outblock of n×x is thinned out with respect to the original block of n×m.However, the present invention may also be applied to a case thevertical direction and horizontal direction are reversed from oneanother, where the thinning-out block of x×n is thinned out with respectto the original block of m×n, by a similar manner.

[0088] Then, the thus-obtained compressed image data having 2×2 blocksmay be further compressed by a well-known BTC (Block Truncation Coding)compressing scheme by which a lossy compressing scheme, and, thereby,the rate of compression of image data can be further improved.

[0089] Next, an image interpolation processing method of carrying outdecompressing of the compressed blocks obtained through imagecompression carried out by thinning-out processing as described abovewill now be described.

[0090] In case an image compressed into the compressed blocks eachhaving 2×2 pixels as shown in FIG. 6A are decompressed into decompressedblocks (corresponding to the original blocks) each having 2×3 pixels,the image data of each pixel of the above-mentioned thinned-out blockwhich includes 2×1 pixels is obtained by interpolation by a nearestpixel method in which image data of pixels of the compressed blocksadjacent to the short sides of the thinned-out block is used fordetermining image data of the pixels of the thinned-out block.

[0091] For example, the thinned-out block ab shown in FIG. 6A has thecompressed blocks gj and kn_(l) adjacent thereto via the short sidesthereof. The compressed block ‘gj’ of 2×2 pixels includes a pixel ‘g’, apixel ‘h’, a pixel ‘i’, and a pixel ‘j’, and the compressed block kn₁ of2×2 pixels includes a pixel ‘k’, a pixel ‘l’, a pixel m_(l), and a pixeln_(l). In this case, the image data of the pixel h adjacent to the upperpixel a of the thinned-out block ab via the short side thereof is usedas it is as the image data of the pixel a. Similarly, the image data ofthe pixel k adjacent to the pixel b of the thinned-out block ab via thebottom short side thereof is used as it is as the image data of thepixel b. Thus, interpolation is performed by the nearest pixel method.

[0092] Accordingly, for example, as shown in FIG. 6B, in case theperpendicular thin line A exists on the pixels g, h, and a, b, k, and l,as the pixel a uses the image data of the pixel h, and the pixel b usesthe image data of the pixel k as mentioned above through interpolation,the 2 pixels a and b can restore the thin line A properly.

[0093] However, if the compressed blocks adjacent to the thinned-outblock via the long sides thereof are used for interpolation, that is,if, for the pixel a, the image data of the pixel e is used, and, for thepixel b, the image data of the pixel f is used, the 2 pixels may be lostfor the thin line A. However, such a method may also be applied.

[0094] In such a case where the interpolation is performed by thenearest pixel method employing compressed blocks adjacent to thethinned-out block via the long sides thereof, both the pixel e and thepixel o are in an equal distance from the pixel a, and, similarly, boththe pixel f and the pixel p are in an equal distance from the pixel b,the following method is employed for determining the pixel to be usedfor the interpolation. That is, the image data of the pixel of thecompressed block which constitutes the adjacent original image block towhich the thinning-out block does not belong is used. Accordingly, forthe pixel a, the image data of the pixel e is used, and, for the pixelb, the image data of the pixel f is used for the interpolation.

[0095] In fact, in a case the horizontal thin line B exists on thepixels c, e, and a, o, and q, as shown in FIG. 6B, when theinterpolation is made by using the image data of the compressed block ofthe 2×2 pixels adjacent to the thinned-out block ab via the long sidethereof, the image data for one pixel of the thin line B can becorrectly restored as, for the pixel a, the image data of the pixel e isused, and, also, for the pixel b, the image data of the pixel f is used.

[0096] However, if, in this case, the interpolation is made by employingthe compressed block adjacent to the thinned-out block ab via the shortside thereof, as, for the pixel a, the image data of the pixel h isused, and, also, for the pixel b, the image data of the pixel k is used,one pixel may be lost for the horizontal thin line B. However, even inthis case, only the number of pixels corresponding to the length of theshort side, i.e., one pixel is lost for one block.

[0097] Thus, by employing the image data of the compressed blockadjacent to the thinned-out block via the short sides thereof forinterpolation, it is possible to efficiently reduce the number of pixelswhich are lost therethrough even when loss of pixels concerning a thinline or an edge line occurs therein. Accordingly, even employing thenearest pixel method, which requires merely a reduced processing time,it is possible to prevent the image quality from remarkably degraded,with effectively reducing the processing time for the interpolation.

[0098] When image size-change (particularly, image magnification)processing is made in case an image after decompression is output, forexample, if the size-change rate (at which the number of pixels ischanged) is larger than a predetermined first threshold (for example,larger than ‘1’, i.e., the number of pixels is increased), a well-knownlinear interpolation method is employed instead of the above-describednearest pixel method. That is, for example, in case the above-mentionedcompressed block of 2×2 pixels is decompressed as shown in FIG. 6A, therespective pixels of the plurality of compressed blocks adjacent to therelevant thinned-out block nearest to the relevant pixel of thethinned-out block are used for determining the image data of therelevant pixel.

[0099] For example, in the example shown in FIG. 6A, for the pixels aand b of the thinning-out block ab, the image data of the nearest pixelsof the compressed blocks ‘cf’ and ‘or’ adjacent to the relevantthinned-out block ab via the long sides thereof are used forinterpolation to determine the image data of the pixels a and b, asfollows:

[0100] As the image data of the pixel a of the thinned-out block ab, theimage data of the average value {(e+o)/2} of the pixels e and o is used;and

[0101] as the image data of the pixel b, the image data of the averagevalue {(f+p)/2} of the pixels f and p is used.

[0102] The reason for employing the linear interpolation instead of thenearest pixel method in case where image magnification processing isperformed is as follows:

[0103] In such a case, when only one pixel is employed for determiningthe image data of a thinned-out pixel according to the nearest pixelmethod, unnaturalness due to the interpolation may become remarkable.Therefore, the linear interpolation method which may provide tonesmoothness more effectively than in the case of employing the nearestpixel method, in general, is applied. Thereby, it may be possible toprevent such unnaturalness from being apparent in thereproduced/decompressed image.

[0104] Furthermore, in case a decompressed image is magnified still moregreatly, i.e., the size-change rate is more than a second predeterminedthreshold (for example, 2, i.e., the number of pixels is increased morethan twice), instead of the linear interpolation method, a third-orderinterpolation method is used in which, by using a three-ordercalculation formula, the image data of the thinned-out pixel(interpolation pixel) is determined by using all the compressed blocksadjacent to the relevant thinned-out block.

[0105] For example, in the example shown in FIG. 6A, in case the pixel aof the thinned-out block ab is determined when the above-mentionedcompressed block of 2×2 pixels is decompressed, the following scheme isapplied:

[0106] In this case, the image data of 16 pixels of all the fourcompressed blocks cf, gj, kn_(l) and or adjacent to the thinned-outblock ab are used.

[0107] Specifically, the following three-order formula (1) is used:

f(a)=f(c)C(x _(c) −x _(a))C(y _(c) −y _(a))+f(d)C(x _(d) −x _(a))C(y_(d) −y _(a))+ . . . +f(q)C(x _(q) −x _(a))C(y _(q) −y _(a))+f(r)C(x_(r) −x _(a))C(y _(r) −y _(a))  (1)

[0108] where:

[0109] f(a) denotes interpolated image data of the pixel a; f(c) denotesthe image data of the pixel c; . . . , f(q) denotes the image data ofthe pixel q; and f(r) denotes the image data of the pixel r. x_(a) andy_(a) denote x-coordinate value and y-coordinate value of the pixel a oncolor chromaticity coordinate plane, respectively. (x_(c), x_(d), . . ., x_(q), x_(r)) and (y_(c), y_(d), . . . , y_(q), y_(r)) denotex-coordinate values and y-coordinate values of pixels c, d, . . . , qand r on the color chromaticity coordinate plane, respectively.

[0110] C(t) is an approximation formulas of a function {sinπt/πt} whichconstitutes a sampling theorem, and one of the following formulas (2),(3) and (4) is applied according to the value of the variable t, asfollows:

C(t)=1−2t ² +|t| ³, in case 0≦|t|<1  (2);

C(t)=4−8|t|+5t ² −|t| ³, in case 1≦|t|<2  (3);

C(t)=0, in case 2≦|t|  (4)

[0111] According to the three-order interpolation method, as theplurality of pixels of compressed blocks present in the periphery of therelevant pixel are utilized, although the processing speed becomesdecreased, it is possible to provide further higher image quality incomparison to the case of employing the linear interpolation method.

[0112] The above-mentioned first and second predetermined thresholdsshould be determined according to various conditions such as imagedisplay performance of an image compression/decompression apparatusused, an observation distance at a time of observation thereof, and soforth. Accordingly, the above-mentioned values (for example, ‘1’ and‘2’) are merely examples.

[0113]FIGS. 10 and 11 are flow charts showing flows of processing of theabove-described image compressing/decompressing methods. That is, FIG.10 is a flow chart illustrating an example of a flow of processingaccording to an image compression technology according to the firstembodiment of the present invention, and FIG. 11 is a flow chartillustrating an example of a flow of image decompression processingaccording to the present invention for decompressing image datacompressed according to the processing illustrated in FIG. 10.

[0114] The flow of the image compression processing shown in FIG. 10will now be described.

[0115] When compressing horizontally original image blocks eachincluding 2×3 pixels which is a unit area to be compressed, the block of2×1 pixels to be thinned out is located in the same position withrespect to each original block (for example, the right end) throughoutthe same line (in a step S1). On the other hand, with respect to thevertical direction, the location of the thinned-out block of 2×1 pixelswith respect to each original block of 2×3 pixels is determined so thatthe thinned-out block is not adjacent to any thinned-out block on theimmediately preceding line (for example, the left end in case thethinned-out block is located at the right end on the immediatelypreceding line) (in a step S2).

[0116] Furthermore, as for the compressed blocks each including 2×2pixels after thinning out the thinning-out blocks each of 2×1 pixelsfrom the original blocks each of 2×3 pixels, lossy compression isperformed thereon based on the BTC method (in a step S3).

[0117] Then, in a step S4, when all the original blocks have notundergone the thinning-out processing, the above-described process(steps S1 through S3) is repeated. After all the original blocks havebeen processed, the image compressing processing is finished.

[0118] The flow of image decompressing processing shown in FIG. 11 willnow be described.

[0119] Image data having 2×2 pixels which is a compressed block is read(in a step S11).

[0120] Then, a size-change rate α (pixel number change rate) on therelevant image for size change processing (pixel number changeprocessing) performed when the decompressed image is output isdetermined (in a step S12).

[0121] In case the size-change rate is not more than the firstpredetermined threshold (for example, “1”), interpolation is performedaccording to the nearest pixel method such that the image data of eachpixel of the thinned-out block is determined from the image data of thepixel adjacent thereto via the short side of the block, as describedabove (in a step S13).

[0122] In case the size-change rate is more than the first predeterminedthreshold (for example, “1”) and also not more than the secondpredetermined threshold (for example, “2”), interpolation is performedaccording to the linear interpolation method such that the image data ofeach pixel of the thinned-out block is determined from the image data ofthe pixels nearest thereto of the plurality of compressed blocksadjacent to the thinned-out block, for example, via the long sidesthereof, as described above (in a step S14).

[0123] In case the size-change rate is more than the secondpredetermined threshold (for example, “2”), interpolation is performedaccording to the three-order interpolation method such that the imagedata of each pixel of the thinned-out block is determined from the imagedata of the respective pixels of all the compressed blocks adjacent tothe thinned-out block, as described above (in a step S14).

[0124] With reference to FIG. 7, image compression scheme andinterpolation scheme according to a second embodiment of the presentinvention in case the number of pixels in a vertical direction ofthinning-out/thinned-out block is equal to or more than three will nowbe described.

[0125] In FIG. 7, in case color image data is compressed, each oforiginal image blocks from which thinning-out blocks are thinnedout/removed includes 3×3 pixels. In the figure, 3×2 pixels shown as awhite portion of each original image block are extracted as a compressedblock after image compression, and 3×1 pixels shown as a hatched portionat the right or left end of each original image block are removed as athinned-out block.

[0126] Specifically, during image data compression according to thesecond embodiment of the present invention illustrated by FIG. 7, on thehorizontal direction, the position of the thinning-out/thinned-out blockwith respect to each original image block is the same for the same line.However, on the vertical direction, the position of thethinning-out/thinned-out block with respect to each original image blockis determined so that the thinning-out/thinned-out block may not beadjacent to or may not align with any thinning-out/thinned-out block onthe immediately preceding line. For example, in the example shown inFIG. 7, the position of the thinning-out/thinned-out block is the rightend with respect to each original image block on the first line, but isthe left end on the second line, then is the right end on the thirdline, . . . By thus proceeding with thinning-out processing by repeatingfor respective lines of original image blocks according to the simplerule, the thinning-out/thinned-out blocks are positioned so that theyare not adjacent to or not aligned with each other, as shown in FIG. 7,for example.

[0127] Also in this embodiment, it is possible that the horizontaldirection and vertical direction are replaced with one another. That is,the position of the thinning-out/thinned-out block is the same on thesame column for the vertical direction, and, the position thereof isdetermined so that the thinning-out/thinned-out block may not adjacentto or may not align with any thinning-out/thinned-out block on theimmediately preceding column.

[0128] Thereby, as the respective thinning-out/thinned-out blocks arenot adjacent to or not aligned with each other between any adjacentoriginal image blocks, a situation that all the pixels arrangedstraightly in horizontal direction or vertical direction are thinnedout/removed by compression processing can be positively prevented.Accordingly, it is possible to prevent thin line/edge lines extendingvertically or horizontally from being lost remarkably through imagecompression and decompression processing. Thus, it is possible tomaintain a high image quality.

[0129] Then, after the above-described thinning-out processing, theabove-mentioned BTC compression (lossy compression) is performed on thecompressed blocks, and, thereby, the compression rate is furtherincreased.

[0130] Image interpolation scheme in image decompression of thethus-obtained compressed image data will now be described.

[0131] According to the second embodiment, as shown in FIG. 7, thenumber of pixels of each thinning-out/thinned-out block in the verticaldirection is more than two. Accordingly, both vertical end pixels of thethinning-out/thinned-out block are determined by the pixels of thecompressed blocks adjacent to the thinning-out/thinned-out block via theshort sides thereof in the nearest pixel method as in theabove-described first embodiment. In contrast thereto, as to theintermediate pixel, the image data thereof is determined by the imagedata of the pixel of the compressed block adjacent to thethinning-out/thinned-out block via the long side thereof but notincluded in the original image block in which the relevantthinning-out/thinned-out block is included.

[0132] Specifically, in the example shown in FIG. 7, thethinning-out/thinned-out block ac of 3×1 pixels includes pixels a, b andc; the compressed block jo of 3×2 pixels includes j, k, l, m_(l), n_(l),and o adjacent to the above-mentioned thinning-out/thinned-out block acvia the top short side thereof; the compressed block pu of 3×2 pixelsincludes p, q, r, s, t, and u adjacent to the above-mentionedthinning-out/thinned-out block ac via the bottom short side thereof; andthe compressed block di of 3×2 pixels includes d, e, f, g, h, and iadjacent to the above-mentioned thinning-out/thinned-out block ac viathe left long side thereof but not included in the original image blockin which the thinning-out/thinned-out block ac is included.

[0133] In this case, according to the above-described scheme, the imagedata of the top pixel a of the thinning-out/thinned-out block ac isdetermined as the image data of the pixel l adjacent thereto on the topside; the image data of the bottom pixel c of thethinning-out/thinned-out block ac is determined as the image data of thepixel p adjacent thereto on the bottom side; and the image data of theintermediate pixel b of the thinning-out/thinned-out block ac isdetermined as the image data of the pixel h adjacent thereto on the leftside.

[0134] Thereby, similarly to the case of the above-described firstembodiment illustrated in FIGS. 6A and 6B, as the pixels of thethinning-out/thinned-out block adjacent to the short sides thereof aredetermined by using the pixels of the compressed blocks adjacent to thethinning-out/thinned-out block via the short sides thereof according tothe nearest pixel method, it is possible to effectively reduce thenumber of pixels lost from thin line/edge line extending verticallyduring image compression and decompression processing.

[0135] Furthermore, as to the intermediate pixel of thethinning-out/thinned-out block, the image data thereof is determined byusing the nearest pixel but adjacent to the pixel to be determined inthe direction other than the direction of the above-mentioned case ofinterpolation manner for the pixels adjacent to the short sides of thethinning-out/thinned-out block. Accordingly, the direction ofinterpolation is not fixed to vertical or horizontal, but variousdirections are used for the interpolation. Thereby, it is possible toeasily maintain the image quality from remarkably degraded.

[0136] Thus, according to the second embodiment, same as in the firstembodiment, as the pixel thinning scheme is improved, it is possible tomaintain a high image quality during image compression and decompressionby interpolation although employing the nearest pixel method whichmerely requires a reduced processing time. Accordingly, it is possibleto attain high speed interpolation processing.

[0137] In the second embodiment, the flows of processing of imagecompression and image decompression are the same as those of theabove-described first embodiment illustrated in FIGS. 10 and 11.However, different from the first embodiment, the original image blockhas 3×3 pixels, and the thinning-out/thinned-out block has 3×1 pixels,as mentioned above. Especially, according to the second embodiment, asthe number of pixels of the thinning-out/thinned-out block along thevertical direction is more than two, image data of the intermediatepixel(s) is determined in decompression processing by using the pixel(s)of the compressed block adjacent to the thinning-out/thinned-out blockbut not included in the original image block in which thethinning-out/thinned-out block is included, as described above.

[0138] Although the above-described second embodiment employs theoriginal block of 3×3 pixels and thinning-out/thinned-out block of 3×1pixels, the basically same concept may be applied to a case where thenumber of pixels along the vertical direction increases more than three,i.e., four, five, . . . That is, the concept of the second embodimentmay also be applied to a case employing the original block of 4×3 pixelsand thinning-out/thinned-out block of 4×1 pixels, . . . In such a case,the number of the above-mentioned intermediate pixels becomes more thanone, i.e., two, three, With reference to FIG. 8, image compressionscheme and interpolation scheme according to a third embodiment of thepresent invention in case the number of pixels ofthinning-out/thinned-out block is half the number of the original imageblock will now be described.

[0139] In FIG. 8, in case color image data is compressed, each oforiginal image blocks from which thinning-out blocks are thinned outincludes 2×4 pixels. In the figure, 2×2 pixels shown as a white portionof each original image block are extracted as a compressed block afterimage compression, and 2×2 pixels shown as a hatched portion at theright or left end of each original image block are removed off as athinned-out block.

[0140] Specifically, during image data compression according to thethird embodiment of the present invention illustrated by FIG. 8, on thehorizontal direction, the position of the thinning-out/thinned-out blockwith respect to each original image block is the same for the same line.However, on the vertical direction, the position of thethinning-out/thinned-out block with respect to each original image blockis determined so that the thinning-out/thinned-out block may not beadjacent to or may not align with any thinning-out/thinned-out block onthe immediately preceding line. For example, in the example shown inFIG. 8, the position of the thinning-out/thinned-out block is the rightend with respect to each original image block on the first line, but isthe left end on the second line. By proceeding with thinning-outprocessing by repeating for respective lines of original image blocksaccording to the simple rule, the thinning-out/thinned-out blocks arepositioned so that they are not adjacent to or not aligned with eachother, as shown in FIG. 8, for example.

[0141] Also in this-embodiment, it is possible that the horizontaldirection and vertical direction are replaced with one another. That is,the position of the thinning-out/thinned-out block is the same on thesame column for the vertical direction, and, the position thereof isdetermined so that the thinning-out/thinned-out block may not adjacentto any thinning-out/thinned-out block on the immediately precedingcolumn.

[0142] Thereby, as the respective thinning-out/thinned-out blocks arenot adjacent to or not aligned with each other between any adjacentoriginal image blocks, a situation that all the pixels arrangedstraightly in horizontal direction or vertical direction are thinnedout/removed by compression processing can be positively prevented.Accordingly, it is possible to prevent thin line/edge line extendingvertically or horizontally from being lost remarkably through imagecompression and decompression processing. Thus, it is possible to easilymaintain a high image quality.

[0143] Then, after the above-described thinning-out processing theabove-mentioned BTC compression (lossy compression) is performed on thecompressed blocks, and, thereby, the compression rate is furtherincreased.

[0144] Image interpolation scheme in image decompression of thethus-obtained compressed image data will now be described.

[0145] In order to obtain a decompressed block of 2×4 pixels from thecompressed block of 2×2 pixels through decompression in the exampleshown in FIG. 8, the above-mentioned thinning-out/thinned-out block isobtained by interpolation by using the pixels of the compressed blocksadjacent to the thinning-out/thinned-out block via the short sidesthereof according to the nearest pixel method.

[0146] Specifically, in the example shown in FIG. 8, thethinning-out/thinned-out block ad of 2×2 pixels includes pixels a, b, cand d; the compressed block il of 2×2 pixels includes i, j, k and ladjacent to the above-mentioned thinning-out/thinned-out block ad viathe top short side thereof; the compressed block m_(l)p of 2×2 pixelsincludes m_(l), n_(l), o and p adjacent to the above-mentionedthinning-out/thinned-out block ad via the bottom short side thereof.

[0147] In this case, according to the above-described scheme, the imagedata of the top pixel a of the thinning-out/thinned-out block ad isdetermined as the image data of the pixel j adjacent thereto on the topside; the image data of the top pixel b of the thinning-out/thinned-outblock ad is determined as the image data of the pixel m_(l) adjacentthereto on the bottom side; the image data of the top pixel c of thethinning-out/thinned-out block ad is determined as the image data of thepixel l adjacent thereto on the top side; the image data of the toppixel d of the thinning-out/thinned-out block ad is determined as theimage data of the pixel o adjacent thereto on the bottom side, as shownin FIG. 8.

[0148] Thereby, similarly to the case of the above-described firstembodiment illustrated in FIGS. 6A and 6B, as the pixels of thethinning-out/thinned-out block adjacent to the short sides thereof aredetermined by using the pixels of the compressed blocks adjacent to thethinning-out/thinned-out block via the short sides thereof according tothe nearest pixel method, it is possible to effectively reduce thenumber of pixels lost from thin line/edge line extending verticallyduring image compression and decompression processing. Thereby, it ispossible to easily maintain the image quality. Thus, even when thinline/edge line is lost through compression and decompression, the numberof pixels lost can be effectively reduced.

[0149] Thus, also according to the third embodiment, same as in thefirst embodiment, as the pixel thinning scheme is improved, it ispossible to maintain a high image quality during image compression anddecompression by interpolation although employing the nearest pixelmethod which requires reduced processing time. Accordingly, it ispossible to attain high speed interpolation processing.

[0150] In the third embodiment, as shown in FIG. 12, when compressinghorizontally original image blocks each including 2×4 pixels which is aunit area to be compressed, the block of 2×2 pixels to be thinned out islocated in the same position with respect to each original block (forexample, the right end) throughout the same line (in a step S21). On theother hand, with respect to the vertical direction, the location of thethinned-out block of 2×2 pixels with respect to each original block of2×4 pixels is determined so that the thinned-out block is not adjacentto or not aligned with the thinned-out block on the immediatelypreceding line (for example, the left end in case the thinned-out blockis located at the right end on the immediately preceding line) (in astep S22).

[0151] Furthermore, as for the compressed blocks each including 2×2pixels after thinning out the thinning-out blocks each of 2×2 pixelshave been thinned out from the original blocks each of 2×4 pixels, lossycompression is made based on the BTC method (in a step S23).

[0152] Then, in a step S24, when all the original blocks have notundergone the thinning-out processing, the above-described process(steps S21 through S23) is repeated. After all the original blocks havebeen processed, the image compressing processing is finished.

[0153] The flow of processing of image decompression is the same as thatof the above-described first embodiment illustrated in FIG. 11. However,different from the first embodiment, the original image block has 2×4pixels, and the thinning-out/thinned-out block has 2×2 pixels, asmentioned above.

[0154] With reference to FIG. 9, image compression scheme andinterpolation scheme according to a fourth embodiment of the presentinvention in case the number of pixels of the thinning-out/thinned-outblock is smaller than half the number of pixels of the original imageblock will now be described.

[0155] In FIG. 9, in case color image data is compressed, each oforiginal image blocks from which thinning-out blocks are thinned outincludes 2×3 pixels. In the figure, 2×1 pixels shown as a white portionof each original image block are extracted as a compressed block afterimage compression, and 2×2 pixels shown as a hatched portion at theright or left end of each original image block are removed as athinned-out block.

[0156] Specifically, during image data compression according to thefourth embodiment of the present invention illustrated by FIG. 9, in thehorizontal direction, the position of the thinning-out/thinned-out blockwith respect to each original image block is the same for the same line.However, in the vertical direction, the position of thethinning-out/thinned-out block with respect to each original image blockis determined so that the compressed block to be left, instead of thethinning-out/thinned-out block, may not be adjacent to or may notaligned with any compressed block on the immediately preceding line. Forexample, in the example shown in FIG. 9, the position of the compressedblock is the left end with respect to each original image block on thefirst line, but is the right end on the second line. By proceeding withthinning-out processing by repeating for respective lines of originalimage blocks according to the simple rule, the compressed blocks arepositioned-so that they are not adjacent to or not aligned with eachother, as shown in FIG. 9, for example.

[0157] Also in this embodiment, it is possible that the horizontaldirection and vertical direction are replaced with one another. That is;the position of the thinning-out/thinned-out block is the same on thesame column for the vertical direction, and, the position of thecompressed block is determined so that the compressed block to be leftmay not adjacent to or may not align with any compressed block on theimmediately preceding column.

[0158] Thereby, as the respective compressed blocks are not adjacent toor not aligned with each other between any adjacent original imageblocks, a situation that all the pixels arranged straightly inhorizontal direction or vertical direction are thinned out/removed bycompression processing can be prevented. Accordingly, it is possible toprevent thin line/edge line extending vertically or horizontally frombeing lost through image compression and decompression processing. Thus,it is possible to maintain high image quality.

[0159] Then, after the above-described thinning-out processing theabove-mentioned BTC compression (lossy compression) is performed on thecompressed blocks, and, thereby, the compression rate is furtherincreased.

[0160] According to the fourth embodiment, in comparison to the firstembodiment, the compression rate can be improved from 1.5 to 3.Accordingly, it is possible to effectively reduce a transmission timefrom the personal computer 20 to the printer apparatus 30.

[0161] Image interpolation scheme in image decompression of thethus-obtained compressed image data will now be described.

[0162] In order to obtain a decompressed block of 2×3 pixels from thecompressed block of 2×1 pixels through decompression in the exampleshown in FIG. 9, the above-mentioned thinning-out/thinned-out block isobtained by interpolation by using the pixels of the compressed blocksadjacent to the thinning-out/thinned-out block via the short sidesthereof according to the nearest pixel method.

[0163] Specifically, in the example shown in FIG. 9, thethinning-out/thinned-out block ad of 2×2 pixels includes pixels a, b, cand d; the compressed block gh of 2×1 pixels includes g and h adjacentto the above-mentioned thinning-out/thinned-out block ad via the topshort side thereof; the compressed block ef of 2×1 pixels includes e andf adjacent to the above-mentioned thinning-out/thinned-out block ad viathe left short side thereof; the compressed block ij of 2×1 pixelsincludes i and j adjacent to the above-mentionedthinning-out/thinned-out block ad via the bottom short side thereof; andthe compressed block kl of 2×1 pixels includes k and l adjacent to theabove-mentioned thinning-out/thinned-out block ad via the right shortside thereof, as shown in the figure.

[0164] In this case, according to the above-described scheme, the imagedata of the top pixel a of the thinning-out/thinned-out block ad isdetermined as the image data of the pixel h adjacent thereto on the topside; the image data of the bottom pixel b of thethinning-out/thinned-out block ad is determined as the image data of thepixel i adjacent thereto on the bottom side; the image data of the toppixel c of the thinning-out/thinned-out block ad is determined as theimage data of the pixel k adjacent thereto on the right side; and theimage data of the top pixel d of the thinning-out/thinned-out block adis determined as the image data of the pixel l adjacent thereto on theright side, as shown in FIG. 9.

[0165] Thereby, similarly to the case of the above-described firstembodiment illustrated in FIGS. 6A and 6B, as the pixels of thethinning-out/thinned-out block adjacent to the short sides thereof aredetermined by using the pixels of the compressed blocks adjacent to thethinning-out/thinned-out block via these short sides thereof accordingto the nearest pixel method, it is possible to effectively reduce thenumber of pixels lost from thin line/edge line extending verticallyduring image compression and decompression processing. Accordingly, thedirection of interpolation is not fixed to vertical or horizontal, butvarious directions are used for the interpolation. Thereby, it ispossible to easily maintain the image quality. Thus, even when thinline/edge line is lost through compression and decompression, the numberof pixels lost can be effectively reduced.

[0166] In each of the above-mentioned second through fourth embodiments,it is also possible to employ the above-described linear interpolationmethod or three-order interpolation method instead of the nearest pixelmethod, as described above.

[0167] Thus, also according to the fourth embodiment, same as in thefirst embodiment, as the pixel thinning scheme is improved, it ispossible to maintain a high image quality during image compression anddecompression by interpolation although employing the nearest pixelmethod which requires reduced processing time. Accordingly, it ispossible to attain high speed interpolation processing.

[0168] In the fourth embodiment, as shown in FIG. 13, when compressinghorizontally original image blocks each including 2×3 pixels which is aunit area to be compressed, the block of 2×2 pixels to be thinned out islocated in the same position with respect to each original block (forexample, the right end) throughout the same line (in a step S31). On theother hand, with respect to the vertical direction, the location of thecompressed block of 2×1 pixels with respect to each original block of2×3 pixels is determined so that the compressed block is not adjacent toor not aligned with any compressed block on the immediately precedingline (for example, the left end in case the thinned-out block is locatedat the right end on the immediately preceding line) (in a step S32).

[0169] Furthermore, as for the compressed blocks each including 2×1pixels after thinning out the thinning-out blocks each of 2×2 pixelshave been thinned out from the original blocks each of 2×3 pixels, lossycompression is made based on the BTC method (in a step S33).

[0170] Then, in a step S34, when all the original blocks have notundergone the thinning-out processing, the above-described process(steps S31 through S33) is repeated. After all the original blocks havebeen processed, the image compressing processing is finished.

[0171] The flow of processing of image decompression is the same as thatof the above-described first embodiment illustrated in FIG. 11. However,different from the first embodiment, the original image block has 2×3pixels, and the thinning-out/thinned-out block has 2×2 pixels, asmentioned above.

[0172] After that, embodiments of how to select one of, and/or tocombine the above-mentioned nearest pixel method, linear interpolationmethod and three-order interpolation method according to positions ofthinning-out/thinned-out pixels to be generated from a compressed blockwith respect to the positions of pixels of the compressed block will nowbe described. According to the schemes of the embodiments which will bedescribed now, it is possible to prevent an image quality from beingremarkably apparently degraded during image compression anddecompression processes, even when relatively large areas are thinnedout through the compression process so as to increase the compressionrate.

[0173]FIG. 14 illustrates a basic interpolation pattern in an imageinterpolation method according to the embodiments which will bedescribed now. With regard to color image data, 5×5 pixels are used as aunit, and, when the 5×5 pixels are generated from 2×2 pixels (indicatedby black in the figure), two types of interpolation methods are used forpixels other than the pixels indicated by black. For example, in casethe pixels (indicated by gray in the figure) are adjacent to the pixelsof the black zone as shown in the figure, the first interpolation methodis applied to generate the pixels of the gray zone while the secondinterpolation method, different from the first interpolation method, isapplied to generated the other pixels (indicated by white).

[0174]FIGS. 12A through 12C illustrate definition of “adjacent pixels”applied to the description below. First, FIG. 12A shows adjacent pixels(gray zone) of image area indicated by black. As shown in the figure,the adjacent pixels are those possessing a side or a vertex of therelevant image area (black zone) in common. The meaning of “in common”in this case is a conceptual one, and, thus, may also be widely appliedto a case respective pixels are spaced from each other. FIG. 12B showsadjacent pixels (gray zone) of the two sides q and q of the relevantimage area (black zone) in case the relevant image zone has arectangular shape as shown in the figure. FIG. 12C shows adjacent pixels(gray zone) of the respective four sides p, q, s and r of the relevantimage area (black zone). A term “pixel group” which will occur alsomeans a single pixel.

[0175]FIG. 16 illustrates one example of image interpolation methodaccording to a fifth embodiment of the present invention. As shown inthe figure, for the gray zone, the interpolation is performed accordingto the nearest pixel method, and, thus, the image data of the adjacentpixel of the black zone is applied as it is so that (1)→(1); (3)→(3);(5)→(5), . . . With regard to the white zone, the linear interpolationmethod is applied, and, thus, ((1)+(2))/2→(9); ((5)+(7))/2→(10);((3)+(4))/2→(11); ((5)+(6))/2→(12); ((7)+(8))/2→(13); ((6)+(8))/2→(14);((12)+(13))/2→(15).

[0176]FIG. 17 shows another example of the image interpolation methodaccording to the fifth embodiment of the present invention. Also in thisexample, same as in the example shown in FIG. 16, the image data of thepixels in the gray zone is determined by the nearest pixel method byusing the image data of the pixels in the black zone as shown in thefigure. However, the image data of the pixels in the white zone isdetermined according to the three-order interpolation method.

[0177] Specifically, assuming that the coordinate system of the originalimage is of X-Y while the coordinate system of the image data aftercoordinate transformation is of X′-Y′, the relationship therebetween canbe expressed by the following formulas (I) and (II) assuming that therelationship between both the coordinate systems is linear:

x=ax′+by′+c  (I);

y=dx′+ey′+f  (II)

[0178] Accordingly, the relationship between both the coordinate systemscan be obtained from calculating of the above-mentioned constants a, b,c, d, e and f by using corresponding actual coordinate values on sixpoints. In the calculation, these six points are not necessarily to belattice points (integral coordinate values).

[0179] Then, by using the above-mentioned formulas (I) end (II), for allthe points of an image obtained after the transformation, correspondingpoints on the original image are obtained, and, color information on thepoints on the original image is used as color information of the pointson the transformed image. However, as all the points on the originalimage may not be lattice points, desired color information should beobtained by using the color information of peripheral lattice points. Insuch a case, the above-mentioned three-order interpolation method isused for obtaining the desired color information by using the colorinformation on the peripheral lattice points.

[0180] Accordingly, the same manner may be applied to the case ofinterpolating pixels in the white zone from pixels in the black/grayzones. Specifically, the pixels (1) through (16) in the black zone shownin FIG. 17 are assumed to be points G through V, and the pixel (17) inthe white zone is assumed to be a point Z. Then, by using image dataf(G) through f(V) on the 16 points G through V, the image data f(Z) onthe pixel (17) is determined through interpolation (third-orderinterpolation), by using the following formulas (III) through (VI):

f(Z)=f(G)C(x _(G) −x _(z))C(y_(G) −y _(Z))+f(H)C(x_(H) −x _(z))C(y _(H)−y _(Z))+ . . . +f(V)C(x _(V) −x _(z))C(y _(V) −y _(Z))  (III);

C(t)=1−2t ² +|t| ³ in case 0≦|t|<1  (IV);

C(t)4−8|t|+5t ² −|t| ³, in case 1≦|t|<2  (V);

C(t)=0, in case 2≦|t|  (VI)

[0181] There, C(t) represents an approximation formula of functionsinπx/πx which expresses a sampling theorem, and the formulas (III)through (VI) are used for each component of R, G, B of color image data.

[0182] According to this method, as information of as many as 16 pointsis used, it is possible to provide a higher-quality image in comparisonto a case of using the linear interpolation method.

[0183] At this time, in case m−x≧3 and n−y≧3 or 2x<m and 2y<n (see FIG.14), a plurality of the above-described interpolation methods areselectively used. This is because, in such a case, it is necessary toselect an appropriate one thereof according to the length of (m−x) and(n−y). For example, when the lengths of (m−x) and (n−y) are smaller(compression rate is smaller), the linear interpolation method (lessfiner interpolation method) may be applied for the white zone, while,when these lengths are larger (compression rate is larger), thethree-order interpolation method (finer interpolation method) may beapplied for the white zone. There, each of m, n, x and y represents thenumber of pixels. In the example of FIG. 14, n=5; m=5, x=2, and y=2. Inthis case, the gray zone (to which the nearest pixel method is appliedas mentioned above) has the width of one pixel, as shown in the figure.This is because, as the image data of the gray zone is generated byusing the black zone as it is according to the nearest pixel method, theimage quality may be degraded if the gray zone has a wide area incomparison to the area of the black zone.

[0184]FIG. 18 illustrates an example of a basic interpolation patternaccording to a sixth embodiment of the present invention. Similar toFIG. 14, 5×5 pixels are used as a unit of color image data, and, bydecompression through interpolation, 5×5 pixels are generated from 2×2pixels in a black zone. Then, for determining pixels other than theblack zone, a plurality of interpolation methods are selectively used.In particular, in the example of FIG. 18, different from theabove-described example shown in FIG. 14, the pixel having a distance βin a center-to-center basis from the pixel in the black zone which islongest among the distances α, β and γ is determined as a white pixel,and, the image data of the pixels in the gray zone are determinedaccording to a first interpolation method while the image data of thepixel in the white zone is determine by a second interpolation methodother than the first interpolation method.

[0185] Specifically, in a example shown in FIG. 19, the nearest pixelmethod is used for the gray zone, and the linear interpolation method isused for the white zone. Thus, the image data of the pixels in the whitezone is determined as the image data of the pixels adjacent theretorespectively, as follow, as shown in the figure: (1)→(1); (5)→(5);(3)→(3); . . . On the other hand, the image data on the pixels in thewhite zone is determined according to the linear interpolation method asfollows: ((1)+(2))/2→(9); ((5)+(7))/2→(10); ((3)+(4))/2→(11);((5)+(6))/2→(12); ((7)+(8))/2→(13); ((6)+(8))/2→(14);((7)+3×(5))/4→(15); ((7)+2×(15))/3→(16); ((7)+(16))/2→(17);((13)+3×(12))/4→(18); ((13)+2×(18))/3→(19); ((13)+(19))/2→(20).

[0186] Also at this time, in case m−x≧3 and n−y≧3 or 2x<m and 2y<n (seeFIG. 18), a plurality of interpolation methods are used. This isbecause, in such a case, it is necessary to select an appropriate onethereof according to the length of (m−x) and (n−y). For example, whenthe lengths of (m−x) and (n−y) are smaller (compression rate issmaller), the linear interpolation method (less finer interpolationmethod) may be applied for the white zone, while, when these lengths arelarger (compression rate is larger), the three-order interpolationmethod (finer interpolation method) may be applied for the white zone.There, each of m, n, x and y represents the number of pixels. In theexample of FIG. 18, n=5; m=5, x=2, and y−2. In this case, the gray zone(to which the nearest pixel method is applied as mentioned above) hasthe width of one pixel, as shown in the figure. This is because, as theimage data of the gray zone is generated by using the black zone as itis according to the nearest pixel method, the image quality may bedegraded if the gray zone has a wider area in comparison to the area ofthe black zone.

[0187]FIG. 20 illustrates an example of a basic interpolation patternaccording to a seventh embodiment of the present invention. Similar toFIG. 14, 5×5 pixels are used as a unit of color image data, and, bydecompression through interpolation, 5×5 pixels are generated from 2×2pixels in a black zone. Then, for determining pixels other than theblack zone, a plurality of interpolation methods are selectively used.In particular, the pixels adjacent to the four sides of the black zoneare determined as those in a gray zone, and, the image data of thepixels in the gray zone are determined according to a firstinterpolation method while the image data of the pixel in the whitezone, other than the black zone and gray zone, is determine by a secondinterpolation method other than the first interpolation method. Byemploying this basic interpolation pattern, it is possible to maintain ahigh image quality particularly for non-edge image part.

[0188] Specifically, in an example shown in FIG. 21, the nearest pixelmethod is used for the gray zone, and the linear interpolation method isused for the white zone. Thus, the image data of the pixels in the grayzone is determined as the image data of the pixels in the black zoneadjacent thereto respectively, as follow, as shown in the figure:(1)→(1); (2)→(2); (4)→(4); (3)→(3); . . . On the other hand, the imagedata on the pixels in the white zone is determined according to thelinear interpolation method as follows: ((2)+(5))/2→(7); and((4)+(6))/2→(8).

[0189] Also at this time, in case m−x ≧3 and n−y≧3 or 2x<m and 2y<n (seeFIG. 20), a plurality of interpolation methods are used. This isbecause, in such a case, it is necessary to select an appropriate onethereof according to the length of (m−x) and (n−y). For example, whenthe lengths of (m−x) and (n−y) are smaller (compression rate issmaller), the linear interpolation method (less finer interpolationmethod) may be applied for the white zone, while, when these lengths arelarger (compression rate is larger), the three-order interpolationmethod (finer interpolation method) may be applied for the white zone.There, each of m, n, x and y represents the number of pixels. In theexample of FIG. 20, n=5; m=5, x=2, and y=2. In this case, the gray zone(to which the nearest pixel method is applied as mentioned above) hasthe width of one pixel, as shown in the figure. This is because, as theimage data of the gray zone is generated by using the black zone as itis according to the nearest pixel method, the image quality may bedegraded if the gray zone has a large area in comparison to the area ofthe black zone.

[0190]FIG. 22 illustrates an example of a basic interpolation patternaccording to an eighth embodiment of the present invention. Similar toFIG. 14, 5×5 pixels are used as a unit of color image data, and, bydecompression through interpolation, 5×5 pixels are generated from 2×2pixels in a black zone. Then, for determining pixels other than theblack zone, a plurality of interpolation methods are selectively used.In particular, in the example of FIG. 22, similar to the above-describedexample shown in FIG. 18, the pixel having a distance β in acenter-to-center basis from the pixel in the black zone which is longestamong the distances α, β and γ is determined as a white pixel, and, theimage data of the pixels in the gray zone are determined according to afirst interpolation method while the image data of the pixel in thewhite zone is determine by a second interpolation method other than thefirst interpolation method. Also the scheme according to this basicinterpolation pattern is advantageous for maintaining a high imagequality for non-edge image parts.

[0191] Specifically, in a example shown in FIG. 23, the nearest pixelmethod is used for the gray zone, and the linear interpolation method isused for the white zone. Thus, the image data of the pixels in the grayzone is determined as the image data of the pixels adjacent theretorespectively, as follow, as shown in the figure: (1)→(1); (2)→(2);(4)→(4); (3)→(3); . . . On the other hand, the image data on the pixelsin the white zone is determined according to the linear interpolationmethod as follows: ((2)+(5))/2→(9); ((4)+(7))/2→(10);((5)+3×(2))/4→(11); ((5)+2×(11))/3→(12); ((5)+(12))/2×(13);((7)+3×(4))/4→(14); ((7)+2×(14))/3→(15); ((7)+(15))/2→(16).

[0192] Also at this time, in case m−x≧3 and n−y≧3 or 2x<m and 2y<n (seeFIG. 22), a plurality of interpolation methods are used. This isbecause, in such a case, it is necessary to select an appropriate onethereof according to the length of (m−x) and (n−y). For example, whenthe lengths of (m−x) and (n−y) are smaller (compression rate issmaller), the linear interpolation method (less finer interpolationmethod) may be applied for the white zone, while, when these lengths arelarger (compression rate is larger), the three-order interpolationmethod (finer interpolation method) may be applied for the white zone.There, each of m, n, x and y represents the number of pixels. In theexample of FIG. 22, n=5; m=5, x=2, and y=2. In this case, the gray zone(to which the nearest pixel method is applied as mentioned above) hasthe width of one pixel, as shown in the figure. This is because, as theimage data of the gray zone is generated by using the black zone as itis according to the nearest pixel method, the image quality may bedegraded if the gray zone has a large area in comparison to the area ofthe black zone.

[0193]FIG. 26 shows a flow chart of operation of the above-describedimage data interpolation method according to the fifth embodiment of thepresent invention. Assuming that 5×5 pixels are regarded as a unit, 2×2pixels of compressed image data are decompressed and restored in a stepS1. Then, the image data of pixels adjacent to these 2×2 pixels or thosebut excluding the farthest pixel(s) are determined through interpolationaccording to a first interpolation method (for example, the nearestpixel method) in a step S2. Then, the image data of the other pixels isdetermined through interpolation according to a second interpolationmethod other than the first interpolation method (for example, thelinear interpolation method), in a step S3.

[0194]FIGS. 24 and 25 illustrate an example of image interpolationmethod according to a variant embodiment of any of the above-describedfifth through eighth embodiments of the present invention in case apixel group generated through interpolation will then undergotransformation processing, such as magnification (increase in the numberof pixels) processing. In such a case, according to the size-change(change in the number of pixels) rate, an appropriate interpolationmethod is set.

[0195] In the example shown in FIG. 24, 2×2 pixels are regarded as aunit, and, the image data on pixels in a white zone is determined byinterpolation. In this case, whether a single interpolation method isapplied, or a plurality of interpolation methods are selectively appliedis determined according to the size-change rate of pixel number changeprocessing which will be performed on the thus generated pixels. Forexample, it is assumed that, a case is assumed where the change-changerate is 2, and, thus, as shown in FIG. 25, the original 2×2 pixels aretransformed into 4×4 pixels.

[0196]FIG. 27 shows a flow chart illustrating the image datainterpolation method according to the above-mentioned variant embodimentof the present invention applied to the above-described case where thesize-change processing will be performed after the interpolation. In thefigure, in a step S11, the compressed data of the 1×1 pixel shown inFIG. 24 is decompressed and restored. Then, the image data of at leastpart (only two pixels having the distances in a center-to-center basisfrom the 1×1 pixel shorter, i.e., a and 7, in the example of FIG. 24,for example) of the pixels adjacent to the 1×1 pixel (first zone orblack zone) is determined according to a first interpolation method (forexample, the nearest pixel method) in a step S12. Then, the image dataof the remaining pixel(s) (the pixel having the distance in acenter-to-center basis from the 1×1 pixel longer, i.e., in the exampleof FIG. 24, for example) is determined according to a secondinterpolation method (for example, the linear interpolation method)other than the first interpolation method in a step S13. Then,processing of changing (increasing in the case shown in FIG. 25) thenumber of pixels is performed on the thus-obtained 2×2 pixels of imagedata, in a step S14.

[0197]FIGS. 28 through 35 show flow charts illustrating theabove-described image data interpolation methods according to ninththrough sixteenth embodiments of the present invention.

[0198] In FIG. 28, in a step S21, pixels in a first zone (black zone inthe example of FIG. 16, for example) are restored by decompression. In astep S22, the image data on pixels (gray zone in the example of FIG. 16,for example) adjacent to the first zone is determined according to afirst interpolation method (for example, the nearest pixel method).Then, in a step S23, the image data on the remaining pixels isdetermined according to a method (for example, the linear interpolationmethod) other than the first interpolation method).

[0199] In FIG. 29, in a step S31, pixels in a first zone (black zone inthe example of FIG. 19, for example) are restored by decompression. In astep S32, the image data on pixels is determined according to aplurality of interpolation methods selectively according to distances ofthe relevant pixels in center-to-center basis from the pixels in thefirst zone (for example, the nearest pixel method is applied to thosenearest to the pixels in the first zone, the linear interpolation methodis applied to those second nearest to the pixels in the first zone, and,then, the third-order interpolation method is applied to the remainingones).

[0200] In FIG. 30, in a step S41, pixels in a first zone (black zone inthe example of FIG. 16, for example) are restored by decompression. In astep S42, an interpolation method(s) to be applied is determinedaccording to the size-change (change in the number of pixels) rate ofpixel number changing processing to be performed later. Then, when it isdetermined in the step S42 that a plurality of interpolation methods areselectively applied, the image data of target pixels is determinedaccording to a first interpolation method (for example, the nearestpixel method, i.e., in case of FIG. 14, for the gray zone) determinedaccording to a predetermined condition (for example, the pixel-numberchange rate of pixel-number processing performed later, or the like, asmentioned above) in steps S43-S44, and, then, the image data on theremaining pixels is determined according to another method (for example,the linear interpolation method or three-order interpolation method forthe white zone) in a step S45. When it is determined in the step S42that a signal interpolation method is applied, the image data of thetarget pixels is determined only according to a single interpolationmethod (for example, the nearest pixel method, the linear interpolationmethod or three-order interpolation method described above) determinedaccording to a predetermined condition (for example, the pixel-numberchange rate of pixel-number processing performed later, or the like, asmentioned above) in a step S46.

[0201] In FIG. 31, in a step S51, pixels in a first zone (black zone inthe example of FIG. 19, for example) are restored by decompression. In astep S52, the image data on pixels (gray zone in the example of FIG. 16,for example) determined from the pixels adjacent to the first zoneaccording to the pixel distances in center-to-center basis from thefirst zone is determined according to a first interpolation method (forexample, the nearest pixel method). Then, in a step S53, the image dataon the remaining pixels is determined according to a method (forexample, the linear interpolation method or third-order interpolationmethod) other than the first interpolation method.

[0202] In FIG. 32, in a step S61, pixels in a first rectangular zone(black zone in the example of FIG. 14, for example) are restored bydecompression. In a step S62, the image data on pixels (gray zone in theexample of FIG. 14, for example) adjacent to two sides of the firstrectangular zone is determined according to a first interpolation method(for example, the nearest pixel method). Then, in a step S63, the imagedata on the remaining pixels is determined according to a method (forexample, the linear interpolation method or third-order interpolationmethod) other than the first interpolation method.

[0203] In FIG. 33, in a step S71, pixels in a first rectangular zone(black zone in the example of FIG. 20, for example) are restored bydecompression. In a step S72, the image data on pixels (gray zone in theexample of FIG. 20, for example) adjacent to the four sides of the firstrectangular zone is determined according to a first interpolation method(for example, the nearest pixel method). Then, in a step S73, the imagedata on the remaining pixels is determined according to a method (forexample, the linear interpolation method or third-order interpolationmethod) other than the first interpolation method.

[0204] In the above-described processes shown in FIGS. 32 and 33,assuming that the above-mentioned first zone is of a rectangle of x×ypixels (shown in FIG. 14, for example), a second zone is of a rectangleof m×n pixels (shown in FIG. 14, for example), preferably 2x<m and also2y<n. Further, the above-mentioned first interpolation method ispreferably applied to the gray zone having the width of not more thanx/2 in the case of process shown in FIG. 32, and the above-mentionedfirst interpolation method is preferably applied to the gray zone havingthe width of not more than x in the case of process shown in FIG. 33.Further, in the process shown in FIG. 32, preferably, m−x≧3 and also n−y≧3.

[0205] In FIG. 34, in a step S81, pixels in a first rectangular zone(black zone in the example of FIG. 18, for example) are restored bydecompression. In a step S82, the image data on pixels (gray zone in theexample of FIG. 18, for example) adjacent to two sides of the firstrectangular zone and also determined according to thecenter-to-center-basis pixel distances from the pixels in the firstrectangular zone is determined according to a first interpolation method(for example, the nearest pixel method). Then, in a step S83, the imagedata on the remaining pixels is determined according to a method (forexample, the linear interpolation method or third-order interpolationmethod) other than the first interpolation method.

[0206] In FIG. 35, in a step S91, pixels in a first rectangular zone(black zone in the example of FIG. 22, for example) are restored bydecompression. In a step S92, the image data on pixels (gray zone in theexample of FIG. 22, for example) adjacent to the four sides of the firstrectangular zone and also determined according to thecenter-to-center-basis pixel distances from the pixels in the first zoneis determined according to a first interpolation method (for example,the nearest pixel method). Then, in a step S93, the image data on theremaining pixels is determined according to a method (for example, thelinear interpolation method or third-order interpolation method) otherthan the first interpolation method.

[0207] The present invention may also be realized by using aninformation recording medium such as a CD-ROM, a magneto-optical disk, aDVD-ROM, a floppy disk, a flash memory, or any other medium such asvarious type of ROM, RAM, or the like in which software programs forcausing a general-purpose computer or the like to perform any of theabove-described image compressing/thinning-out, imagedecompression/interpolation processing schemes according to theabove-described embodiments of the present invention. In such a case,the above-mentioned information recording medium is loaded into ageneral-purpose computer or the like, which then reads the softwareprograms therefrom, writes them into a memory thereof, again reads outthe programs therefrom in appropriate timing so as to appropriatelyexecute the relevant processing schemes.

[0208] Further, the present invention is not limited to theabove-described embodiments, and variations and modifications may bemade without departing from the scope of the present invention.

[0209] The present application is based on Japanese priorityapplications Nos. 2000-396434 and 2001-91594, filed on Dec. 27, 2000 andMar. 28, 2001, respectively, the entire contents of which are herebyincorporated by reference.

What is claimed is:
 1. An image compressing apparatus comprising: a partperforming pixel thinning-out operation and compressing image data; anda part determining a position of pixel to be thinned out along a firstdirection depending on the position thereof along a second directionperpendicular to the first direction.
 2. The apparatus as claimed inclaim 1, wherein the position of pixel to be thinned out along the firstdirection has a predetermined relationship with the position thereofalong the second direction.
 3. The apparatus as claimed in claim 1,wherein the position of pixel to be thinned out comprises a positionwith respect to each unit area of the relevant image including apredetermined number of pixels.
 4. The apparatus as claimed in claim 3,wherein the positions of pixels to be thinned out along the firstdirection are determined along the second direction so that thepositions of pixels to be thinned out do not align with one anotherbetween each pair of unit areas adjacent to one another along the seconddirection.
 5. An image decompressing apparatus comprising: a partinterpolating thinned-out pixels; and a part determining pixels to beused for the interpolation, wherein said part determining the pixel tobe used for interpolation determines such that pixels nearest to thethinned-out pixels may be selected therefor.
 6. The image decompressingapparatus as claimed in claim 5, wherein said part determining the pixelto be used for interpolation for thinned-out pixels determines such thatpixels not included in an original pixel block in which the thinned-outpixels are included may be selected therefor.
 7. The image decompressingapparatus as claimed in claim 5, wherein said part determining the pixelto be used for interpolation determines such that pixels adjacent to anoriginal pixel block via short sides thereof may be selected.
 8. Animage decompressing apparatus comprising: a part performinginterpolation of thinned-out pixels; and a part determining a method ofthe interpolation according to a pixel-number changing rate ofpixel-number changing processing performed after the interpolation suchthat a finer interpolation method be selected as the pixel-numberchanging rate at which the number of pixels is increased becomes larger.9. The image decompressing apparatus as claimed in claim 8, wherein anearest pixel method is selected when the pixel-number changing rage isless than a first threshold, a linear interpolation method is appliedwhen the pixel-number changing rate falls within a range between thefirst threshold and a second threshold, and a three-order interpolationmethod is applied when the pixel-number changing rate is more than thesecond threshold.
 10. An image decompressing apparatus comprising: apart interpolating thinned-out pixels from not-thinned-out pixels; and apart determining an interpolating method applied, wherein said partdetermining an interpolating method applied applies a less finerinterpolation method for thinned-out pixels located nearer to thenot-thinned-out pixels used for the interpolation.
 11. The imagedecompressing apparatus as claimed in claim 10, wherein said partdetermining an interpolating method applied selectively applies aplurality of interpolation methods and determines the interpolationmethod to be applied according to the center-to-center pixels distancesfrom the not-thinned-out pixels.
 12. The image decompressing apparatusas claimed in claim 10, wherein said part determining an interpolatingmethod applied applies a nearest pixel method for thinned-out pixelsnearest to the not-thinned-out pixels used for interpolation, applies atleast one of a linear interpolation method and a third-orderinterpolation method for the other pixels.
 13. An image compressingmethod comprising the steps of: a) performing pixel thinning-outoperation and compressing image data; and b) determining positions ofpixels to be thinned out along a first direction depending on thepositions thereof along a second direction perpendicular to the firstdirection.
 14. The method as claimed in claim 13, wherein the positionsof pixels to be thinned out comprise positions with respect to each unitarea of the relevant image including a predetermined number of pixels.15. The method as claimed in claim 14, wherein the positions of pixelsto be thinned out along the first direction are determined along thesecond direction so that the positions of pixels to be thinned out donot align with one another between each pair of unit areas adjacent toone another along the second direction.
 16. An image decompressingmethod comprising the steps of: a) interpolating thinned-out pixels; andb) determining pixels to be used for the interpolation, wherein saidstep b) determines such that pixels nearest to the thinned-out pixelsmay be applied.
 17. The method as claimed in claim 16, wherein said stepb) determines such that pixels not included in an original pixel blockin which thinned-out pixels are included may be applied forinterpolation of the thinned-out pixels.
 18. The method as claimed inclaim 16, wherein said step b) determines such that pixels adjacent toan original pixel block in which thinned-out pixels-are included viashort sides thereof may be applied for interpolation of the thinned-outpixels.
 19. An image decompressing method comprising the steps of: a)performing interpolation of thinned-out pixels; and b) determining amethod of the interpolation according to a pixel-number changing rate ofpixel-number changing processing performed after the interpolation suchthat a finer interpolation method be selected as the pixel-numberchanging rate at which the number of pixels is increased becomes larger.20. The image decompressing method as claimed in claim 19, wherein anearest pixel method is applied when the pixel-number changing rage isless than a first threshold, a linear interpolation method is appliedwhen the pixel-number changing rate falls within a range between thefirst threshold and a second threshold, and a three-order interpolationmethod is applied when the pixel-number changing rate is more than thesecond threshold.
 21. An image decompressing method comprising the stepsof: a) interpolating thinned-out pixels from not-thinned-out pixels; andb) determining an interpolating method applied, wherein said step b)applies a less finer interpolation method for thinned-out pixels locatednearer to the not-thinned-out pixels used for the interpolation.
 22. Themethods as claimed in claim 21, wherein said step b) selectively appliesa plurality of interpolation methods and determines the interpolationmethod to be applied according to the center-to-center pixels distancesfrom the not-thinned-out pixels.
 23. The method as claimed in claim 21,wherein said step b) applies a nearest pixel method for thinned-outpixels most nearest to the not-thinned-out pixels used forinterpolation, but applies at least one of a linear interpolation methodand a third-order interpolation method for the other pixels.
 24. Acomputer-readable information recording medium having a software programrecorded therein to be read by a general-purpose computer so as to causethe computer to perform the steps of: a) performing pixel thinning-outoperation and compressing image data; and b) determining positions ofpixels to be thinned out along a first direction depending on thepositions thereof along a second direction perpendicular to the firstdirection.
 25. The computer-readable information recording medium asclaimed in claim 24, wherein the software program is such that thepositions of pixels to be thinned out comprise positions with respect toeach unit area of the relevant image including a predetermined number ofpixels.
 26. The computer-readable information recording medium asclaimed in claim 24, wherein the software program is such that thepositions of pixels to be thinned out along the first direction aredetermined along the second direction so that the positions of pixels tobe thinned out do not align with one another between each pair of unitareas adjacent to one another along the second direction.
 27. Acomputer-readable information recording medium having a software programrecorded therein to be read by a general-purpose computer so as to causethe computer to perform the steps of: a) interpolating thinned-outpixels; and b) determining pixels to be used for the interpolation,wherein said step b) determines such that pixels nearest to thethinned-out pixels may be selected.
 28. The computer-readableinformation recording medium as claimed in claim 27, wherein thesoftware program is such that said step b) determines such that pixelsnot included in an original pixel block in which thinned-out pixels areincluded may be applied for interpolation of the thinned-out pixels. 29.The computer-readable information recording medium as claimed in claim27, wherein the software program is such that said step b) determinessuch that pixels adjacent to an original pixel block in whichthinned-out pixels are included via short sides thereof may be appliedfor interpolation of the thinned-out pixels.
 30. A computer-readableinformation recording medium having a software program recorded thereinto be read by a general-purpose computer so as to cause the computer toperform the steps of: a) performing interpolation of thinned-out pixels;and b) determining a method of the interpolation according to apixel-number changing rate of pixel-number changing processing performedafter the interpolation such that a finer interpolation method beselected as the pixel-number changing rate at which the number of pixelsis increased becomes larger.
 31. The computer-readable informationrecording medium as claimed in claim 30, wherein the software program issuch that a nearest pixel method is applied when the pixel-numberchanging rage is less than a first threshold, a linear interpolationmethod is applied when the pixel-number changing rate falls within arange between the first threshold and a second threshold, and athree-order interpolation method is applied when the pixel-numberchanging rate is more than the second threshold.
 32. A computer-readableinformation recording medium having a software program recorded thereinto be read by a general-purpose computer so as to cause the computer toperform the steps of: a) interpolating thinned-out pixels fromnot-thinned-out pixels; and b) determining an interpolating methodapplied, wherein said step b) applies a less finer interpolation methodfor thinned-out pixels located nearer to the not-thinned-out pixels usedfor the interpolation.
 33. The computer-readable information recordingmedium as claimed in claim 32, wherein said step b) selectively appliesa plurality of interpolation methods and determines the interpolationmethod to be applied according to the center-to-center pixels distancesfrom the not-thinned-out pixels.
 34. The computer-readable informationrecording medium as claimed in claim 32, wherein the software program issuch that said step b) applies a nearest pixel method for thinned-outpixels most nearest to the not-thinned-out pixels used forinterpolation, but applies at least one of a linear interpolation methodand a third-order interpolation method for the other pixels.